There are aspects of New Product Development (NPD) business processes that pose particularly difficult challenges to Organizational Learning systems. Short product and process life cycles compress the available time window for recouping the expenses associated with product development. Cross-functional collaboration in product development organizations requires the merging of knowledge from diverse disciplinary and personal skills-based perspectives. Cross-institutional collaboration leads a requirement for knowledge to be combined from participants across multiple collaborating organizations. Transient existence in teams and high turnover results in a reduction in organizational knowledge unless there is a repository for knowledge rather than a dependence on knowledge which is situated in the minds of individuals.
Trang 1in Product Development Organisations
Brian Donnellan,
Analog Devices B.V., Limerick, Ireland
brian.donnellan@analog.com
Brian Fitzgerald
University of Limerick, Ireland
bf@ul.ie
Abstract: There are aspects of New Product Development (NPD) business processes that pose particularly difficult challenges
to Organizational Learning systems Short product and process life cycles compress the available time window for recouping the expenses associated with product development Cross-functional collaboration in product development organizations requires the merging of knowledge from diverse disciplinary and personal skills-based perspectives Cross-institutional collaboration leads a requirement for knowledge to be combined from participants across multiple collaborating organizations Transient existence in teams and high turnover results in a reduction in organizational knowledge unless there is a repository for knowledge rather than a dependence on knowledge which is situated in the minds of individuals
High rates of change in turbulent industries, such as electronics, motivates participants in NPD processes to effectively overcome these Organizational Learning challenges The potential payoff includes time saved by not repeating mistakes and reuse of knowledge that leads to successful products and processes IS research has paid little attention to NPD processes despite the fact that some IS appears to have the potential to have an impact in that area
Recent research completed by these researchers in Analog Devices Inc identified Organizational Learning challenges encountered by engineering teams in product development This paper will report on these challenges and will describe how systems were developed to support organizational learning to support the product development process
Keywords: Organizational Learning, New Product Development, Knowledge Management, Knowledge Management Systems
1 Introduction
There are aspects of New Product
Development (NPD) business processes that
pose particularly difficult challenges to
Knowledge Management Systems (KMS)
Short product and process life cycles
compress the available time window for
learning lessons associated with product
development Cross-functional collaboration in
product development organizations requires
the merging of knowledge from diverse
disciplinary and personal skills-based
perspectives Cross-institutional collaboration
leads to a requirement for knowledge to be
combined from participants across multiple
collaborating organizations Transient
participation in teams and high turnover results
in a reduction in organizational knowledge
unless there is a repository for knowledge
rather than a dependence on knowledge which
is situated in the minds of individuals
When these challenges are not overcome they
result in inefficiencies in NPD business
processes The inefficiencies may have
several negative influences on the
performance of NPD organizations There can
be a lack of shared understanding among the
NPD team members There may be an
over-reliance on transmitting explicit rather than tacit
design information that can, in turn, lead to
repeated mistakes or a re-invention of
solutions during product evolution Skills that
had been developed due to collaboration may
be also lost thereafter because of the inability
to transfer existing knowledge into other parts
of the organization Inefficiencies also arise from inconsistencies in multiple versions of information located in different locations
High rates of change in turbulent industries, such as electronics, motivates participants in NPD processes to effectively overcome these
KM challenges The potential payoff includes time saved by not repeating mistakes and reuse of knowledge that leads to successful products and processes
IS research has paid little attention to NPD processes despite the fact that some IS appears to have the potential to have an impact in that area Recent research completed by the authors of this paper in Analog Devices Inc (ADI)1 identified KM problems encountered by engineering teams in product development These challenges pointed to the need to adopt a dual approach
to knowledge management The approach demands (a) a supporting infrastructure of IS applications and (b) management initiatives to promote appropriate behavioural patterns that help create a one-company culture
1 Analog Devices Inc is a world leader in the design, manufacture, and marketing of integrated circuits (ICs) used in signal processing applications Founded in 1965, ADI employs approximately 8,500 worldwide
Trang 2This paper will report on the KMS challenges
faced by engineering teams engaged in NPD
and will outline the balanced approach to KM
adopted by ADI that incorporates both
technical and socio-technical systems to support the product development process The paper is structured as follows:
Table 1: Structure of this Paper
Section Topic
1 Introduction
2 New Product Development and Knowledge Management Systems
3 KM Challenges posed by NPD Processes
4 ADI’s Response to KMS Challenges
5 Summary, Conclusions
2 New product development and
knowledge management
systems
This section will review current thinking on KM
in the context of NPD and will describe some
of the KMS models proposed for organizations
engaged in NPD
2.1 Knowledge management and new
product development
Seminal contributions to research into the role
of knowledge in competition have come from
Drucker and Grant Drucker was one of the
first to herald a knowledge-based economy by
illustrating that knowledge was eclipsing
traditional factors of production (i.e land,
labour and capital) as a primary resource He
was credited with coining the term “knowledge
worker” and in (Drucker 1993) stated,
“knowledge had become the basic economic
resource” Support for Drucker’s viewpoint
came throughout the 1990’s as a more general
view of the pervasive role of knowledge in
business activities evolved from a number of
management writers and practitioners For
example, (Quinn 1992) provides statistical
support for the information and
knowledge-based view of the economy (e.g services
sector accounts for 74% of value-added in the
U.S economy, estimating that 65-75% of those
engaged in manufacturing employment are
actually engaged in services) Similarly,
(Stewart 1997) supports this assertion that
information and knowledge are the economy’s
primary resource with numerous statistics and
examples in both his book’s foreword and first
chapter
Grant proposed a “resource-based” view of the
firm This view emphasizes the importance of a
firm’s resources, including intellectual capital,
as its source of sustainable competitive
advantage In (Grant 2000) he states “what
distinguishes the Knowledge Economy from
previous economies is the sheer accumulation
of knowledge by society, the rapid pace of
innovation and, most important, the advent of
digital technologies that have had far-reaching
implications for the sources of value in the modern economy” He identifies four aspects
of management practice which are impacted
by the dynamics of the emergent Knowledge Economy:
a) Property rights in knowledge Recognition of the value of proprietary knowledge has increased the amount of intellectual property legislation by legislatures and judicial systems over the past two decades The enforcement of intellectual property in the form of patents, copyrights, and trademarks has become a central asset-management activity (Grindley and Teece 1997)
b) Accelerating knowledge creation and application
Companies engaged in new product development have struggled to shorten their product development cycles For example, the fundamental force behind Intel’s sustained success is its “time pacing” - the time pacing of product development though continual minor innovation with periodic “mid-life kickers”, together with nine-month fabrication cycle (Brown and Eisenhardt 1998)
c) Converting tacit into explicit knowledge Kogut and Zander coined the term
“paradox of replication” to describe where the codification of knowledge required for internal replication may also facilitate replication of that knowledge by other firms (Kogut and Zander 1992) The challenge facing KM practitioners appears to be how
to build barriers to external replication through linking internal systems to knowledge that cannot be replicated by outsiders (Schultze 1998)
d) Competing for standards Over the last two decades, there has been
a change in attitude towards the role of industry standards Firms are now more willing to sacrifice short-term financial gains for long-term benefits derived from standardization processes These strategies can imply that firms have to form collaborative projects with customers, competitors and government agencies to
Trang 3achieve a standardization goal These
types of projects, by their nature, place a
lot of emphasis on KM capabilities
2.2 Knowledge management systems
and new product development
There are three common applications of IS to
KM initiatives: (1) the coding and sharing of
best practices, (2) the creation of corporate
knowledge directories, and (3) the creation of
knowledge networks There is much debate on
the effectiveness of these IS contributions in
supporting KM initiatives Some argue that
capturing knowledge in a KMS can inhibit
learning and results in the same knowledge
being applied to different situations even when
it might not be appropriate (Cole 1998) Other
researchers contend that the application of IS
can create an infrastructure and environment
for strengthening and accelerating KM
initiatives by actualizing, supporting,
augmenting and reinforcing knowledge
processes by enhancing their underlying
dynamics, scope, timing and synergy (Vance
and Enyon 1998), (Hendriks and Vriens 1999)
Research in KMS has paid little attention to
NPD processes despite the fact that KMS
technology appears to have the potential to
have an impact in that area Ramesh and
Tiwana analysed the NPD process for a
Personal Digital Assistant operating system,
and went on to develop a prototype system to
support collaborative NPD (Ramesh and
Tiwana 1999)
Court, Culley et al investigated the use of
information in NPD teams and reported on the
use of information technology to support the
product development process (Court, Culley et
al 1997) They analyzed the methods by which the NPD team members retrieve, apply and subsequently transfer their information A significant finding was that even though team members have access to IS tools and services, they still preferred to use manual and verbal methods of communication and information retrieval These preferred formats may suggest that computer information accessing and storage is still at the infancy stage and therefore used with some reluctance by design teams A key challenge appeared to the researchers to be the extensive use of personal information stores and the absence of easy-to-use indexing systems
Scott proposed a framework that decomposed the NPD process into three phases and then classified the types of knowledge and IS appropriate for each phase (Scott 1996) (see Table 2) The first phase is the pre-product phase and the knowledge requirements at this phase are related to what has been learned about these types of products in the past and how that learning can be applied to the planned project Groupware and intranets are seen as IS support systems that can help this phase The second phase is concerned with the actual product design activity and focuses
on the design decisions that are made and the
IS that can provide decision support The third and final phase focuses on production issues that arise after design Product data management IS are seen are relevant at this stage, as well as Video Conferencing to help coordinate production planning
Table 2: Knowledge in New Product Development (Scott 1996)
Pre-product Design Product Design Post-product Design
Knowledge
Lessons learned Projects history Links to Experts Customer needs Supplier competence Market intelligence
Product design rationale Process design rationale Causes for problems and failures in product testing
Manufacturability Product testing Root causes for Engineering Changes
IS Groupware Intranets
Simulations Prototypes Prod Data Mgmt Syst
Videoconferencing
Prod Data Mgmt Syst
Video Conferencing
The same author used Nonaka’s SECI model,
in combination with a model for
cross-department coordination (Adler 1995) to
develop a framework to describe IS support for
New Product Development in the electronics
industry The framework is depicted in Figure
1
Nonaka’s “socialization” knowledge creation mode and Adler’s “teams”- type coordination mechanism requires face-to-face interaction for the transfer of tacit knowledge that is difficult to articulate, communicate, formalize and encode ((Nonaka 1991), (Adler 1995) (Winter 1987), (von Hippel 1994)) Software models of the product under development
Trang 4enhance the “externalization” knowledge
creation mode by making tacit understandings
of specifications explicit The prototype
becomes a source of discussion for “mutual
adjustment” coordination mechanisms (Adler
1995) and prevents misunderstandings from
perpetuating The “internalization” knowledge
creation mode depends on experimentation
with multiple “plans” Computer simulations
help engineers convert explicit knowledge
(originating across boundaries) to tacit
knowledge with many iterations of “what if”
scenarios Engineers vary parameters and test
performance creating new knowledge without
the need to build physical models In the
“combination” mode of knowledge creation,
Product Data Management Systems (PDMS)
represent explicit knowledge, which is
objective and easy to encode, and enables its
transformation to further explicit knowledge
using Adler’s “standards” type of coordination
mechanism
Some empirical work has been done on
analyzing knowledge management in new
product development processes Anderson et
al look at the design activity in Rank Xerox and illustrate how collaborative, inter-actional, and organizational ordering are not addressed
by the information technology infrastructure in the Design Dept at Rank Xerox (Anderson, Button et al 1993) Adler et al argue for a process-oriented approach to new product development and use a case study of a fictitious company, which represented a composite of a number of companies studied
by Adler (Adler, Mandelbaum et al 1996) He claims that the process oriented approach, which had cross-functional teams as a central element, led to the creation of best practice templates which in turn led to greater efficiencies in product development Van de Ven and Polley empirically demonstrate how the early stages of product development projects can be accounted for by using principles drawn from chaos theory – providing potential future insight into the front end of new product development efforts that traditionally have proven elusive (van de Ven and Polley 1992)
Socialization Externalisation Internalisation Combination
Mutual
Plans
Simulations
Standards Product Data Management Systems Explicit Knowledge
Tacit to Tacit Tacit to Explicit Explicit to Tacit Explicit to Explicit
Figure 1: IS to support New Product Development (Scott 1996)
The next section will identify and describe
some of the KMS challenges encountered by
organizations engaged in New Product
Development
3 The KMS challenges faced by
NPD processes
Todays NPD activities pose interesting
challenges for KMS initiatives This section will
describe some of those challenges
3.1 Demands for increased productivity in new product development
NPD processes may have short product and process life cycles These cycles are getting shorter and they are compressing the available time window for recouping the expenses associated with product development This places a premium on the ability to effectively capture knowledge created during the process
so that it can be re-used in the next generation
of products to reduce development time This capture-reuse cycle is a key enabler for productivity improvements in the design phase
of product development
Trang 5Figure 2: Rate of Product Development in Electronics (Moore’s Law)
Figure 2 shows that the number of transistors
per chip doubles every 18 - 24 months
However it has been estimated that
productivity2 among electronic design
engineers doubles every 36 months (Collett
1998) The competitive pressure to improve
productivity and thereby reduce the product
development cycle time is huge Since the
challenges associated with capturing and
reusing knowledge are, by their nature,
knowledge management challenges – this is
one of the key KM challenges being posed by
NPD KMS responses to this challenge range
from the application of knowledge “codification”
systems to knowledge “personalization”
systems [Hansen, 1999 #1262]
3.2 Internal knowledge transfer
Today’s NPD organizations need to facilitate
knowledge transfer across internal
organizational boundaries The drive to enable
this knowledge transfer may stem from any
one of a number of factors: the existence of
“virtual teams” that are geographically
dispersed, the re-organization of NPD activities
from a linear to a concurrent model or the need
for stronger communication flow between
organizational units that had been
disconnected heretofore e.g sales and
manufacturing
3.2.1 Virtual product development teams
NPD organizations can be distributed across
geographical boundaries In the case of ADI,
there are product development centers in the
USA, Ireland, India, and China The product
2
† Productivity = Dollar Value-add per Unit of Engineering
Effort in the U.S Semiconductor Industry 1986 – 1995
Source: U.S Census and Bureau of Labor and Statistics
development activity that spans these centers requires the teams to share their knowledge across team boundaries It also creates a need for KMS infrastructure to support and promote knowledge sharing The challenges posed by distributed teams may arise from cultural differences The appreciation of cultural differences across geographically dispersed teams may be a key factor in the success of those teams There are at least four ways in which culture influences the behaviours central
to knowledge management in virtual product development teams:
a) Culture shapes assumptions about what knowledge is and which knowledge is worth managing Sackman empirically demonstrated four different kinds of cultural knowledge: “dictionary” knowledge, “directory” knowledge, “recipe” knowledge and “axiomatic” knowledge (Sackmann 1992) Hedlund and Nonaka contrasts U.S and Japanese practices of managing knowledge (Hedlund and Nonaka 1993) The basis for the contrast
is the cultural difference between U.S and Japanese firms
b) Culture defines the relationships between individual and organizational knowledge, determining who is expected to control specific knowledge, as well as who must share it and who can hoard it This relationship is influenced by what some researchers refer to as the presence of an atmosphere of “care” in a company “Care” can be characterized by an active empathy, access to help and lenience in judgement Organizations can foster helping behaviour in their workers by training them in pedagogical skills and intervention techniques Help can become
an element of their performance appraisals
Trang 6and talk about how people are helping
each other can be encouraged Von Krogh
and Roos stress that knowledge nurturing
and creating organizations should be
caring organizations (von Krogh and Roos
1996) They are characterized for having a
propensity to help, as well as lenience or a
capacity to accept errors and for being
reciprocal Altogether, these
characteristics give rise to a trustworthy,
empathetic and helpful organization culture
in which knowledge is the basic aspect
Culture can also promote unique attitudes
toward communication and information,
which in extreme cases can restrict
knowledge transfer to the point of
organizational demise as demonstrated by
(Brown and Starkey 1994)
c) Culture creates the context for social
interaction that determines how knowledge
will be shared in particular situations
Knowledge that is introduced to an
organization is often purchased with cash,
but for knowledge that is generated
internally, the currency is reciprocity
Davenport and Prusak describe three
different roles that workers assume in an
organization’s knowledge market economy
(Davenport and Prusak 1997):
- Buyers in the market are seeking information
to solve a complex problem Buyers will look to
people with knowledge and who are willing to
share it and will also seek sellers who have
exchanged knowledge with them in the past
- Sellers in the market have the information
about a product or service that will benefit the
buyers In a market where hoarding knowledge
is rewarded, the price for buying knowledge is
too high because sellers are unwilling to sell
- Knowledge brokers spend a lot of time
gathering their information through various
means and channels
Reducing harsh bureaucratic structures and
increasing informal communication may
empower creativity and innovation by
promoting spontaneity, experimentation and
freedom of expression (Graham and Pizzo
1996) This culture entails an almost total
removal of many of the values that
underpinned the reengineering and “right
sizing” management culture of the early
1990’s For example, knowledge cultures value
a “fat” middle management layer for
professional support and a tolerance for the
functional inefficiency that a messy, chaotic
creative process implies (Baskerville and
Pries-Heje 1998)
Culture shapes the processes by which the new knowledge with its accompanying uncertainties is created, legitimated, and distributed in organizations In this context Hayduck developed a framework of organizational practices to foster knowledge sharing that is based on sensitivities to the national culture in which a firm finds itself located (Hayduk 1998) She referenced Hofstede’s work and asserts that his work could be used to identify the dimensions of management that influence the success or failure of knowledge management initiatives In particular, she referred to Hofstede’s identification of masculinity and individualism
as the predominant “dimensions of management” endemic to American culture and describes how these cultural traits place a strong emphasis on the need to fulfill obligations of interest and self-actualization She went on to describe a program of organizational practices - systems, structures and processes, which would help overcome cultural barriers to knowledge management
3.2.2 Cross-functional collaboration
Many NPD projects require cross-functional collaboration The nature and importance of this collaboration is described by Wheelwright and Clark as follows:
“Outstanding product development requires effective action from all of the major functions in the business From engineering one needs good designs, well-executed tests, and high quality-proto-types; from marketing, thoughtful product positioning, solid customer analysis, and well-thought-out product plans; from manufacturing, capable processes, precise cost estimates and skilful pilot production and ramp-up Great products and
processes are achieved when all of these activities fit well together The firm must develop the capability to achieve integration across the functions in a timely
and effective way.” p.165 (Wheelwright and Clark 1992)
The patterns of communication are described
in Table 3 The ends of the spectra represent opposites in integration On the left is a communication pattern that is sparse, infrequent, one-way, and late One the right, the communication is rich, frequent, reciprocal, and early This is the preferred mode of communication for NPD organizations because collaborating engineers meet face to face with their colleagues early in the design process
Trang 7and share preliminary ideas with sketches, models, and notes
Table 3: Communication between Functional Groups in NPD (Wheelwright and Clark 1992)
Dimension of
Communication
Range of Choice
Richness of Media Sparse: documents, computer networks Rich: face-to-face, models
Frequency Low: One-shot, batch High: piece-by-piece, on-line, intensive
Timing Late: completed work, ends the process Early: preliminary, begins the process
3.3 External knowledge transfer
3.3.1 Cross-institutional collaboration
Cross-institutional collaboration is also
becoming quite common in NPD processes
The need for this type of collaboration arises
when organizations seek to collaborate with
sources of knowledge, which are external to it
For instance a firm may want to work with an
internationally recognized centre-of-excellence
in an academic institution with which it has no
formal relationship Cases where NPD teams
want to work closely with external standards
organizations are also becoming more
prevalent In such cases knowledge has to be
combined from participants across multiple
collaborating organizations
3.4 Transient team membership
NPD teams are staffed with people who may
possess much sought-after skills and
expertise Consequently there can be high
turnover rates in NPD organizations, as firms
compete for staff with highly rated R&D
experience The resulting transient existence
of teams results in a reduction in
organizational knowledge unless there is a
repository for knowledge rather than a
dependence on knowledge that is solely
situated in the minds of individuals
There is also a requirement, however, that
some staff turnover should exist for product
development teams to be effective The rate of
movement of staff members across
organizational boundaries has been shown to
have an effect on NPD team output Katz
explored the relationship among the mean
tenure of product development teams, the
degree of external communication, and
performance (Katz 1982) In his study of 50
product development teams in a large American corporation, he found that initially group performance increased with increasing mean tenure of the group, but this relationship reversed and performance dropped off after five years The decline in performance was significantly correlated with a decline in external communication and a growth in so-called Not-Invented-Here (NIH) behavior (Brown and Eisenhardt 1995)
3.5 Knowledge to support NPD stage gate processes
A stage-gate process is a conceptual and operational road map for moving a new-product project from idea to launch (Cooper 1994) What differentiates stage-gate NPD processes from other NPD processes is that decision-making events follow each stage Gates are meetings where the project undergoes a thorough examination and after which executive management decides whether
to incur more R&D expense in the project or not NPD teams complete a prescribed set of related cross-functional tasks in each stage before obtaining management approval to proceed to the next stage of product development The gates represent control points where teams’ plans are repeatedly re-assessed in the light of the additional information that emerges during the life-cycle
of the project Researchers who have recognized that different phases of the NPD process may demand different KMS requirements include (Adler, Mandelbaum et
al 1996), (Scott 1996), and (Yang and Yu 2002) The diagram in Figure 3 describes a typical NPD stage-gate process and indicates the critical decisions made at the different stages
Trang 8Stage 1 Stage 2 Stage 3 Stage 4
“What should we do?” “Can we do it?” “How?” “Just do it?” Figure 3: NPD Stage-Gate Process (adapted from (Shake 1999))
There has been some attention paid by
researchers to the identification of the types of
knowledge required by a new product
development activity Table 4 lists the main contributors and their categorization of NPD knowledge types
Table 4: Knowledge needed in NPD Processes
Researcher Types of NPD Knowledge
(Eder 1989) Prescriptive (know-how), Descriptive (know-that)
(Nonaka 1991) Explicit and Tacit with four knowledge conversion processes: socialization, externalization, combination and internalization
(Orlikowski 2000)
Knowing the organization, Knowing the players in the game, Knowing how to coordinate across time and space, Knowing how
to develop capabilities, Knowing how to innovate (Rodgers and Clarkson 1998) Tacit, Explicit, Operative, Substantive, Heuristic, Algorithmic, Deep, Shallow
(Scott 1996) Pre-project, product and process design, manufacturing
(Rajagopalan and Subramani 2002) Agents, Actions, Agency, Context, Purpose, Lessons for the Future
(Ullman 1992) General, Domain Specific, Procedural
(Vincenti 1990) Fundamental Design Concepts, Criteria/Specifications, Theoretical tools, Quantitative/Physical data, Practicalities
The KMS challenge for NPD organizations is to
recognize that different types of knowledge are
appropriate for different phases of an NPD
process Once this realization has been
achieved, the next challenge is concerned with
ensuring that the sources of that knowledge
are available to the NPD teams at the
appropriate milestones in the stage gate
process
4 ADI’s response to KMS
challenges in NPD
4.1 A portfolio of KMS applications to
address different KM challenges
There are two common applications of IS to
support codification and personalization in
product development – the use of “codified”
design libraries (codification) and the creation
of corporate knowledge networks or “yellow
pages” (personalization) These approaches
are shown in Figure 4 The diagram shows
three dimensions The “explicitness” dimension
shows the degree of tacitness vs explicitness
of the knowledge being addressed by a KMS
The “reach” dimension shows the range of effectiveness of the knowledge transfer mechanism The “KMS” dimension shows the scope of the KMS application, ranging from personalization to codification “Yellow Pages”
are shown as spanning the communication space from individuals to groups in an organization Such systems are not exported outside an organization because of the threat
of loss of key individual contributors to competitors The systems are positioned close
to the tacit dimension because they enable people-to-people (tacit) knowledge transfer
“Design libraries” are shown at the other extremes of the diagram The libraries span the communication space between groups and other organizations because they may be packaged in a format suitable to delivery as intellectual property to either internal groups or external groups (or both) They are close to the explicit dimension because they represent an attempt to codify the knowledge associated with a product i.e a people-to-documents approach
Trang 9“Meta-knowledge” is located between the two
extremes and is focused on intermediation
Intermediation refers to the connection of
people to people It is the brokerage function of
bringing together those who seek a certain
piece of knowledge with those who are able to
provide that piece of knowledge It is
interpersonal focus positions intermediation
primarily within the realm of tacit knowledge
transfer It occupies the communication space
between individuals and groups in an
organization and lies between the tacit and
explicit dimensions Through the use of
meta-knowledge, the documents become more like
databases where search, retrieval, and reuse
of text elements (explicit knowledge) are
promoted while also giving the reader the
opportunity to contact the source of the
knowledge so that they may have a dialogue to
enable tacit knowledge transfer (Braa and Sandahl 2000)
A conceptual framework showing the relative contribution spaces of EnCore and docK is shown in Figure 4 The vertical axis describes
“knowledge” as it ranges from tacit, at one extremity, through metaknowledge, to explicit knowledge at the other extreme The horizontal axis describes organizational
“reach”, ranging from the individual, at one extremity, through group, organization and ultimately to other organizations In this context, “reach” is intended to convey the range of applicability of different KMS The Z-axis describes the spectrum of types of KMS, from personalization through harvesting to codification The three KMS applications are mapped onto the framework in Figure 4
Harvesting
docK
EnCore
Yellow Pages
Reach
Group Individual
Personalization
Codification
Organization Inter-Organization
KMS Approach
Knowledge
The KMS shown in Figure 4 are:
a) “Yellow Pages” are WWW-based systems
used to locate employees in an
organization based on attributes such as
knowledge, affiliations, education, or
interests (Carrozza 2000) Where these
systems are used, staff profiles are created (either by the staff themselves or
by a facilitator) These profiles are structured in a manner that renders them easily searchable and retrievable across the organization The central goal of the
Trang 10systems is to enable staff members to
easily identify other staff members who
share common interests These types of
systems are located close to the ”tacit” and
“personalization” extremes of the
conceptual framework because they are
concerned with enabling direct
human-to-human knowledge exchange
b) “EnCore” is a repository for reusable
product development IP In Figure 4, it is
located close to the “codification” and
“explicit” values on the KMS and
knowledge axes respectively because it is
concerned with codified, explicit IP
elements These elements are capable of
being reused across the organization or
even exported to other organizations
(hence its position on the “reach” axis)
c) “docK” is a KMS designed to locate and
retrieve metaknowledge It is a catalog
with entries describing knowledge creation
events in ADI In Figure 4 it is located
close to the “harvesting” and
“metaknowledge” values on the KMS and knowledge axes respectively The system may be most effectively used to create opportunities for knowledge flow across internal organization units and hence its location on the “reach” axis
4.2 Peer reviews as “Knowledge Events” in NPD stage-gate processes
Each of the “gates” in an NPD process represents a peer review with a “go” or “no go”
outcome Since the majority of costs are incurred in the latter stages of a project, and since companies do not want to “spend good money on a bad idea”, the process should include a pause for reviewing all learnings after each stage The outcome of each gate is a critical decision to either continue or abort the process This citical decision is illustrated in Figure 5
Critical Decision (Go/No Go)
Risk
Cost
100%
50%
0%
Risk/Cost
Time
Figure 5: Decisions in a Stage Gate Process (adapted from (Shake 1999))
Bergquist, Ljungberg and Snis draw attention
to the potential offered by peer reviews as a
mechanism for knowledge dissemination
(Bergquist, Ljungberg et al 2001) In
particular, they conclude from their analysis of
peer reviews in a pharmaceutical company,
that the reviews “play an important
coordination role in workers’ daily knowledge
activities” Furthermore, the collaborative effort
involved in peer reviews has the effect of
legitimizing new knowledge by
“organizationally sanctioning it and thereby
creating a platform for collective
sense-making.”
4.3 Summary and conclusions
The challenges listed above have a significant effect on key NPD performance metrics and researchers (e.g (Ramesh and Tiwana 1999), (Macintosh 1997)) are starting to identify the detrimental effects of poor knowledge management on NPD organization performance Their research concludes that sub-optimum knowledge management in NPD teams can lead to situations where highly-paid workers spend too much time looking for needed information because essential know-how is available only in the hands of a few employees or else is buried in piles of documents and data To make matters worse,